Download Stock Prices and Implied Abnormal Earnings Growth

International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
Stock Prices and Implied Abnormal Earnings Growth
Hafiz Imtiaz AHMAD
NYIT, Abu Dhabi, UAE.
Email: [email protected]
Pascal ALPHONSE
University of Lille North of France, F-59000,
Lille, France-LSMRC. Email: [email protected]
Michel LEVASSEUR
University of Lille North of France, F-59000,
Lille, France-LSMRC. Email: [email protected]
ABSTRACT: In terms of corporate valuation, the frequently used heuristics are Price Earnings or
Price Earnings to Growth ratios. The development of a valuation model of type Abnormal Earnings
Growth Model including modeling of expected rents evolution, conditions compatible with perfect
competition, allows us to propose a testable relationship between market value of share, expected
earnings per share in a year, its rate of growth in short term and a set of accounting variables
composing a synthetic indicator of growth of company. Our results show that (1) expected increase in
earnings per share are significantly associated with stock prices for developed countries, (2) but, the
persistence of its effects is limited for emerging countries, (3) when the dynamics of growth are more
complex, inclusion of synthetic variable of can make a significant correction term (4) and the implied
cost of capital is significantly higher for emerging countries than for developed countries.
Keywords: equity valuation; abnormal earnings; Emerging markets
JEL Classifications: G12; G14; M41
1. Introduction
Our study examines the relationship between the market price of a share, expected earnings and its
expected growth for the next two years because they are the very value drivers, followed by the
financial community through the P/E ratio and PEG ratio, for example. Consistent with the current
accounting literature called, the association. We take the proposal put forward by Barth et al.
(2001): “an accounting amount is defined as value relevant if it has a predicted association with equity
market values” (p.79) and their following remark; “accounting information can be value relevant but
not decision relevant if it is superseded by more timely information”. We make no assumption
regarding the efficiency of stock markets. Our study fits in the course of all those interested to price
levels and not their changes. We raise this by a double question: knowing that the form of association
between stock price and expected earnings per share depends on the type of growth of the company, (i)
that brings short term increase in expected earnings by financial analysts to explain differences in stock
market value (ii) can an indicator of growth built on historical accounting data correct the bias
introduced by previous measure?
The interest in this subject is primarily motivated by practical considerations. Investments in the
international equity markets have become significant for fund managers worldwide. The use of methods
based on comparison of basic observed ratios, for listed companies, between stock prices and expected
earnings per share is often considered the most powerful, (Liu et al, 2007) reports that “EPS forecasts
represented substantially better summary measures of value than did OCF forecasts in all five countries
examined, and this relative superiority was observed in most industries”. Understanding the link
between market value and expected earnings is likely to illuminate the investment process in countries
where information is more difficult to collect for foreign investors.
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Stock Prices And Implied Abnormal Earnings Growth
The second motivation is of theoretical nature. It focuses on the relationship between book values
and market values. The valuation models based on abnormal earnings growth (A.E.G.) provide support
to the link between expected future earnings, expected dividends and market values. The pioneering
model of Ohlson and Juettner-Nauroth (2005) claim that only the expected earnings for the next two
years and expected dividend are sufficient. The empirical evidence is not conducive to this hypothesis
(Gode and Mohanram, 2003), (Penman, 2005). The question is whether an extension of the model
A.E.G.(Abnormal Earnings Growth) proposing a more fine decomposition of the abnormal earnings
growth in volume and intensity provides a better estimate of the link between expected earnings and
stock price of a share.
We begin our study with a theoretical extension of the model A.E.G. Aware of the fact that the
models of type AEG are complex in their inner mechanics (Brief, 2007), we want to make development
of the profitability in the form of a progressive realization of a set of growth opportunities. To do this,
we take an idea developed by Walker and Wang (2003) in a different context, that of R.I.M. (Residual
Income Models). As Walker and Wang, we bring together the microeconomic analysis and modeling of
accounting earnings. But we do so as a part of valuation based on taking into account expected earnings
and especially their growth.
The second part of the study is empirical. Three samples are formed over the period 19982008.They include American companies, firms from other developed countries (Germany, Australia,
Canada, France, Japan, and the United Kingdom) and a set from emerging countries (China, Korea,
Hong Kong, India, Malaysia, Singapore, Taiwan and Thailand). Our objective is to provide an
international comparison. From historical accounting data, we build a synthetic indicator of growth by
company. We, then, proceed to estimate our model by incorporating the variables of expected earnings
(in level and in variation), this synthetic variable of growth and other control variables. The objective is
to verify (1) that the anticipated effects of abnormal earnings growth are limited in time, (2) that the
inclusion of the synthetic variable for growth makes a significant correction when the variable of
growth in the short-term alone is insufficient,(3) that the values implicit of cost of capital are
acceptable from an economic stand point.
Our empirical study allows to establish the following results:
(i)
Whatever the geographical zone, expected earnings per share remains the variable most
strongly associated with the stock market values. But, the coefficients are higher in
developed countries than in emerging countries. The valuation of profits is affected by
different levels of their persistence and more generally of risk.
The expected change in earning per share is significantly associated with the market value of a share
(especially for developed countries) but its persistence is limited (especially in emerging countries).
This last result contrary to the intuition which would like the expected growth being greater in
emerging countries, the PEG is a better tool of valuation in these countries. The PER and PEG ratio
combine in valuation essentially, within developed countries.
(ii)
These two indicators must be supplemented to avoid either over-valuation or undervaluation. Taking into account the intensity of the growth through historical accounting
indicators provides a part of the missing information. The corrections are mostly positive
(insufficient to take into account the growth potential by the increase of expected earnings,
especially in emerging countries) and more rarely negative (low persistence of the intensity
of the expected pension, rather in part of developed countries).
(iii)
At the international level, the expected implied rates of return are significantly higher in
emerging countries than in developed countries.
The rest of the paper is organized as follows. In Section 2, we develop our model; Section 3 presents
our data and some descriptive statistics. Section 4 describes the methods of calculation of the variable
of growth. Our results are presented in Section 5 and Section 6 concludes.
2. The Model
2.1 The sources of model:
We take an idea developed by Walker and Wang (2003) in a different framework. Walker and Wang
approach to microeconomic analysis and modeling of company’s accounting earnings particularly the
R.I.M. (Residual Income Model). They studied several forms of competition and provide, among other,
a representation of the dynamic followed by the residual income in a world of perfect competition. We
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International Journal of Economics and Financial Issues, Vol. 4, No. 1, 2014, pp.196-216
propose a similar extension but applied to the model AEG (Abnormal Earning Growth) proposed by
Ohlson and Juettner-Neuroth (2005).
We preferred to place our study in the current A.E.G. model because its point of departure is linked
to an empirical observation. The accounting variable best associated with market value is expected
earnings (Ohlson & Gao, 2006). Unlike the R.I.M. model that bases valuation on the book value of
equity, the A.E.G. model anchor valuation in the capitalization of expected earnings (Ohlson J.A.,
2005). The progress in the modeling requires a description of the dynamics of this earnings. Ohlson and
Juettner Neuroth postulate that the annual variation in the expected abnormal earnings (income in
excess of the remuneration of reinvested cost of capital) follows an autoregressive process of order 1.
Not only, no theoretical justification is advanced to support this hypothesis, but this is certainly very
restrictive, as it gives only expected incomes very close role in valuation.
The purpose of this article is to extend the analysis of Walker and Wang to the model of Ohlson and
Juettner Neuroth in the framework of a pure and perfect competition and unbiased accounting. The
originality of this paper is inspired by a measure of growth, already used in accounting literature by
Hribar and Yehuda (Hribar & Yehuda, 2008). Thus indirectly taking into account the expected rents,
we, partly, believe to avoid some of the shortcomings highlighted by Holthausen and Watts
(Holthausen and Watts, 2001).
2.2 The valuation model from abnormal earnings growth and growth opportunities
First we assume that the price of a share is equal to the sum of free cash flow received by
shareholders
discounted at a required rate:
P = ∑∞
(
(1)
)
A second hypothesis, the variation in earnings has two sources: the variation in the value of a rent
and reinvestment of undistributed profits. The complementary hypothesis of the reinvestment of the
latter at the rate r guarantees the neutrality of the dividend policy. By designating, intensity of expected
rent by a and q its extent, we put:
EPS
− EPS = a
∙q
− a ∙ q + (EPS − FPS ) ∙ r (2)
This particular set of assumptions used to express the price of share based on the expected
income, the required rate of return and expected values of the parameters defining the future rent:
=
+ ∙∑
(
[
]
∙
(
[ ∙ ])
)
(3)
To complete the model, we adopt a third hypothesis that the variables a and q follow linear
informational dynamics described in (4). The intensity of the rent a
is decomposed into a part
depending on its past value δ ∙ a and a white noise ε , .
Its persistence is measured by the parameter δ (with the condition 0 < < 1 to take into
account the effects of competition). The extent of the rent q
is a function of its trajectory q
and a
gap which itself decomposes into a corrective movement back toward the track γ ∙ (1 + c) ∙ (q − q )
and a white noise ε , . The coefficient γ measures the intensity of the restoring force to the track q .
The trajectory q of the extent of the rent grows at a rate c to take account of the growth. Finally, the
two white noises embedded in these movements are assumed to be independent: there is no link
between variations of intensity and variations of the extent of the rent.
= ∙ + ,
−
= ∙( + )∙( − )+ ,
(4)
(
)
= ∙ +
,
= ∀ ,
,
,
This set of assumptions allows to write the following relationship (Proof available)
=
−( + )∙
∙ ∙
+
∙ [ ]∙ ∙
(5)
with :
g = (1 + c) ∙ δ ∙ γ − 1
ℎ = (1 + c) ∙ δ ∙ (1 − γ) ∙ [δ ∙ (1 + c) − 1]
CEPS = EPS + r ∙ FPS
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Stock Prices And Implied Abnormal Earnings Growth
The primary interest of this model is to retain the general form of popular valuation models, taking
as anchoring the expected earnings per share. For example, if δ = γ = 1, it reduces to the model of
Ohlson Juettner-Nauroth which is only a special case. Assuming again that E EPS = (1 + c) ∙
E EPS , we find the standard model of Gordon and Shapiro.
The second interest of this model is mainly to clarify the value of the coefficient included in the
autoregressive dynamics of abnormal earnings growth. It is not solely equal to the expected rate of
growth in the long run, as in Ohlson and Juettner-Nauroth. It takes into account the value creation
potential of the firm, the speed with which the latter will be realized (γ) and its ability to persist (δ).
The third interest is to show that under what conditions a valuation based only on expected earnings
EPS and EPS may suffice. It is necessary that the term h is near to zero or that δ ∙ (1 + c) = 1.
Conversely, when the ability to generate value is not persistent (δ < (1 + c) ), a model of type AEG
overestimates the share. When the enterprise is only at the beginning of growth ( q high), its
implementation very progressive (γ low) and its ability to create value very persistent (δ > (1 + c) ),
then a model of type AEG is very incomplete. Its explanatory power is weak and suffers from the
absence of key variables.
2.3 The specification of the model tested
From an empirical point of view, the measures selected for
and
are the
median forecasts of earnings per share retained by IBES, noted
and
.The measure chosen for
[ ] is the median forecast adopted by IBES for dividend per share, noted
.We do not have any
[
].
direct forecast for
∙
The objective of this study is to test the explanatory power of several
approximations:
∙ [ ]=∑
∙ ∙
(6)
Where k is one of the N variables potentially correlated with the expected abnormal earnings
growth, Y knowing that α is a measure of its expected impact on the evolution of the earnings and
TAPS total assets per share. P is the share price in the beginning of the year. The
variablesP ,EPS ,EPS and DPS were divided by TAPS , to be normalized. Finally, the model was
completed by the inclusion of a control variable for size measured by log of market capitalization in
U.S. dollars. The following specification was chosen
=
+
∙
+
∙
∙
+∑
∙
+
∙
(
)+
(7)
One of the main limits of this specification is that it only takes the average values for r and g with in
each country. Note that according to the theoratical model we should have
r=
3.
β
∙β
+
β
−
β
∙β
and g = − .
Data and Descriptive Statistics
3.1 Constitution of the samples
Our sample was compiled from the information available in early July 2009 in the data base
Thomson Financial Accounting Research data and covering 18 countries for which the number of firms
represented in this database was the highest, it is possible some information has been modified ex post
by data provider. It contains both the developed countries (Germany, Australia, Canada, France, Italy,
Japan, United Kingdom, Sweden and USA) and emerging countries (Brazil, China, Korea, Hong Kong,
India, Malaysia, Singapore, Taiwan, and Thailand). South Africa and India were eliminated from
sample due to too few and limited forecast data. In order to study the period 2001-2008 between the
two crises, it was necessary to collect the data over the period 1998-2008. In effect some variables
appear in the form of annual variations, other as average of past performance. Missing information,
especially for forecast of earning per share, reduced the sample size.
In order to constitute homogenous sample with in each of the country as regards of accounting year,
we selected only the companies with year-end corresponding to the date most widely used in the
country. Generally, it is the 31 December, with the exception of Australia (end of June) and Japan (end
of March). This requirement generally seems not very constraining.
199
International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
Table 1. Selection of Sample
This table presents the modalities of selection of companies studied. The period of selection extends from 1998 to 2008.The data comes from Worldscope and IBES databases
provided by Thomson Financial. The securities initially selected for all concerned countries are those considered by Thomson Financial as active or inactive, in order to limit the
“survivorship” bias. Numbers of these securities correspond to firms effectively disappeared, to not listed companies or yet to particular categories of securities issued. The
selection process consisted of a search of market values year after year of these companies and to retain only the firms years for which this information was available. In order to
have uniform accounting periods by country, we have selected only those companies that adopted the most usual year end date for each country. By following the sector
classification proposed by Fama and French (49), we have eliminated all societies of financial sectors and real estate (45-49) and the companies from which the sector was not
identified. The following selection consisted of to retain only the firms for which accounting data and earnings per share forecast, necessary for the study was available
Active
and
inactive in
the
database
Thomson
Financial
Number of
firms whose
fiscal year
end date is
known
The most
frequent end
of year for the
country
Number of
firms having
this year end
date
Percentage of
firms with
this year end
date
Number of
firms with a
code FF
sector less
than 45
Number of
companies with
market
capitalizations
available at least
for one year
Number of firms
/ year with
known market
capitalizations b
etween 1998 and
2008
Number of firms
/ year with the
known book
values used
between 1998
and 2008
Number of
firms/ year
Number of firms
with equity
Number of firms /
/ year with
&capitalizatio year with positive
positive net
n in excess of net income between
income between
1 million $
1998 and 2008
2001 and 2008
between 1998
&2008
Number of
firms/ year
with EPS
forecasts
available
between 2001
and 2008
USA
28 013
8 574
December
6 086
70.98%
4 531
4 217
32190
30 888
25 127
15 910
12 078
5 940
Germany
Australia
29 096
17 369
7 075
2 733
December
June
6 739
1 975
95,3%
72,3%
6 066
1 660
546
1 376
4 624
8 163
2 457
6 668
2 386
5 831
1 807
2 613
1 424
2 287
705
851
Canada
France
Italy
20 176
27 856
13 825
5 665
5 750
1 705
December
December
December
5 076
4 781
1 640
89,6%
83,1%
96,2%
4 282
4 131
1 422
937
470
210
6 342
4 099
1 648
3 962
2 534
1 287
3 790
2 417
1 280
2 168
1 924
967
1 778
1 603
762
840
812
356
Japan
United Kindom
36 774
38 141
5 604
7 201
2 969
3 976
53,0%
55,2%
2 652
3 454
2 564
702
24 453
4 869
10 979
4 771
10 876
4 316
9 176
2 650
8 167
2 107
3 818
985
11 050
194 287
1 772
37 505
March
December
December
1 633
28 789
92,2%
1 441
25 108
309
7 114
2 276
56 474
1 054
33 712
1 048
31 944
776
22 081
599
18 727
409
8 776
21 722
23 521
7 335
4 437
7 318
4 381
99,8%
98,7%
6 615
4 081
250
1 768
1 957
10 682
1 008
2 493
974
2 421
787
2 047
647
1 672
252
381
Korea
Hong Kong
Indonesia
1 804
7 155
888
1 091
1 240
716
998
805
716
91,5%
64,9%
100,0%
956
624
570
948
469
274
7 691
3 787
2 228
5 603
3 565
2 049
5 482
3 390
1 781
4 235
2 378
1 362
3 570
2 020
1 139
376
675
232
Malaysia
Singapore
1 938
6 053
1 450
1 610
918
1 146
63,3%
71,2%
794
1 014
510
354
3 859
2 564
3 188
2 128
3 073
2 066
2 338
1 581
1 962
1 319
519
340
3 754
1 084
67 919
1 894
800
20 573
1 891
755
18 928
99,8%
94,4%
1 795
641
17 090
1 418
413
6 404
9 725
3 191
45 684
4 605
2 618
27 257
4 589
2 444
26 220
3 630
1 944
20 302
3 071
1 606
17 006
628
424
3 827
Sweden
Other developed countries
Brazil
China
Taiwan
Thailand
Emerging countries
December
December
December
December
December
December
December
December
December
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International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
The percentage of companies respecting this practice is most often above 90%.However, there
are two major exceptions among the developed countries (Japan and United Kingdom, where the
percentage is around 50%). Similarly, Hong Kong and Malaysia have smaller proportions (about 60%).
The financial and real estate companies whose accounting standards are often specific and not
comparable were eliminated. We could raise within the Thomson Financial database only the market
capitalization for
7 114 companies of the other developed countries and 6 404 companies of emerging countries, for a
total firms-year respectively equal to 56 474 and 45 684. Companies are not, therefore, present for all
years. If we compare these figures to theoretical value of firms-year with a continuous presence over 11
years, we obtain a frequency of occurrence of 72% for other developed countries and 65% for emerging
countries. This last sample is, therefore, somewhat less dense.
The availability of accounting data required to estimate the variables used in the study further
reduced the sample size. The loss of the number of observation is equivalent for the two sub
populations (other developed countries and emerging countries), or about 40%. For the rest of the study,
we selected only profitable companies. They are more numerous in emerging countries (77%) than
among other developed countries (69%). Finally, the greatest loss of observation comes from the
limited number of forecasts for earning per share available on IBES during this period. The coverage
rate is 47% for other developed countries and only 23% for the emerging countries. In total, we have
12 603 firm years distributed for 8 776 to other developed countries and 3 827 for emerging countries.
The number of observation is increasing over the period: 802 in 2001 and 1809 in 2008 but relatively
stable from 2004 to 2008.The maximum is 2175 in 2007, just before the last financial crisis.
3.2 Descriptive statistics
The average stock market values normalized by total assets (measured by the item
WS.YrEndMarketCap divided by the item WS.TotalAssets of Worldscope database from Thomson
Reuters) are substantially similar for emerging countries (1.09) and other developed countries
(1.10).The medians are lower because of the asymmetry of the distributions associated with positive
sign of this measure. With in groups, the averages are significantly different: the highest for Australia
(1.47) and Indonesia (1.36) and the lowest for Italy and Japan (0.84) and Korea (0.77).The mean and
median are higher in the case of USA (1.55 and 1.13 respectively), reflecting a higher capitalization
and /or greater indebtedness over this period.
The return (measured by the item IBH.EPSMedianFYR1 divided by (WS.TotalAssets/
WS.Common Shares Outstanding) of the databases Worldscope and IBES from Thomson Reuters)
appear higher for the emerging countries (0.103) and USA (0.01) than for other developed countries
(0.075) if we consider expected earnings per share normalized by total assets per share. Brazil emerges
as the best performing country (0.14) and Japan as the least (0.04).The ratio of the expected change in
earnings per share normalized by total assets per share (measured by the difference of
IBH.EPSMedianFYR2
and
IBH.EPSMedianFYR1,
divided
by
(WS.TotalAssets/
WS.CommonSharesOutstanding) of the databases Worldscope and IBES from Thomson Reuters)
reinforces this impression. It is higher for the USA (0.018) and emerging (0.014) than for other
developed countries (0.10), Brazil and Japan still occupying the same places.
The sample firms belonging to other developed countries are sized (measured by the logarithm of
market capitalization in USD: WS.YrEndMarketCapUSD of Worldscope database from Thomson
Reuters) a little larger than those of emerging countries, but smaller than the American ones. The
companies are significantly smaller for Malaysia, Thailand and Singapore.
201
International Journal of Economics and Financial Issues, Vol. 4, No. 1, 2014, pp.196-216
Table 2. Descriptive Statistics
This table presents the synthesis of the values taken in the sample by the 3 basic selected variable used in the
chosen model, i.e. market capitalization at year end, expected earnings per share for the coming year and expected
earnings growth for the following year .All these variables are normalized by total assets for the first, by total
assets divided by number of shares for the following two. The table also presents a measure of the size of
companies selected through the natural logarithm of the market capitalization. The sample contains for all the
countries only the companies whose year end is 31 December (30 June for Australia and 31 March for Japan). The
study period extends from 2001-2008.The data come from Worldscope and IBES databases provided by Thomson
Financial
Panel A :
USA
Market capitalization / Total
assets
Mean
Median
S.D
1.55
1.13
1.37
Expected EPS / Total Assets
per share
Mean
Median
S.D
0.10
0.08
0.09
Eaxpected EPS Variation / Total Assets
per sahre
Mean
Median
S.D
0.018
0.012
0.026
Germany
Australia
Canada
France
Italy
Japan
United
Kingdom
Sweden
Mean
1,11
1,47
1,11
0,99
0,84
0,84
1,23
0,72
1,06
0,90
0,70
0,67
0,64
0,96
1,19
1,36
0,80
0,93
0,66
0,68
0,96
0,07
0,11
0,08
0,07
0,05
0,04
0,09
0,06
0,08
0,06
0,05
0,05
0,04
0,07
0,06
0,10
0,06
0,04
0,03
0,03
0,07
0,012
0,017
0,009
0,009
0,007
0,006
0,009
0,008
0,010
0,005
0,007
0,006
0,004
0,007
0,015
0,036
0,027
0,012
0,008
0,007
0,023
1,22
1,10
0,98
0,83
1,03
0,95
0,09
0,075
0,08
0,061
0,05
0,055
0,012
0,010
0,010
0,007
0,018
0,018
Brazil
China
Korea
Hong-Kong
Indonesia
Malaysia
Singapore
Taiwan
Thaïland
Mean
0,96
1,11
0,77
1,24
1,36
1,09
1,01
1,27
0,98
1,09
0,77
0,76
0,55
0,90
0,82
0,75
0,81
0,97
0,77
0,79
0,72
1,14
0,80
1,06
1,58
1,11
0,73
1,02
0,79
0,99
0,14
0,08
0,08
0,09
0,13
0,10
0,10
0,11
0,10
0,103
0,09
0,07
0,07
0,08
0,11
0,08
0,09
0,10
0,08
0,086
0,37
0,06
0,06
0,07
0,10
0,07
0,06
0,08
0,06
0,103
0,021
0,012
0,012
0,014
0,015
0,011
0,017
0,012
0,011
0,014
0,015
0,007
0,008
0,009
0,013
0,009
0,013
0,008
0,009
0,010
0,031
0,022
0,021
0,027
0,028
0,016
0,021
0,031
0,021
0,024
Panel B :
Size
Variation of sales over 2
years in %
Ratio of invetsment over 2
years compared to
depreciation allowances
Mean
Median
S.D
1.35
1.10
0.87
Mean
7.72
Mean
0.39
Median
0.25
Germany
Australia
Canada
France
Italy
Japan
United
Kingdom
Sweden
Mean
6,91
6,05
7,14
7,00
7,37
7,21
0.22
0.69
0.56
0.25
0.25
0.13
0.16
0.33
0.29
0.16
0.17
0.10
0.31
1.26
0.95
0.34
0.34
0.17
-0.02
0.28
0.15
0.02
-0.08
0.01
-0.08
-0.06
-0.05
-0.08
-0.12
-0.02
0.33
1.27
0.67
0.41
0.25
0.13
1.14
2.04
1.88
1.22
1.23
1.20
1.02
1.30
1.42
1.12
1.00
1.10
0.63
2.70
1.72
0.69
0.81
0.56
6,96
0.35
0.21
0.62
0.03
-0.11
0.73
1.26
1.02
0.93
6,77
6,93
0.31
0.34
0.20
0.20
0.47
0.56
-0.03
0.04
-0.13
-0.08
0.52
0.54
0.99
1.37
0.90
1.11
0.58
1.08
Brazil
China
Korea
Hong-Kong
Indonesia
Malaysia
7,65
6,97
7,37
6,93
6,32
5,44
0.43
0.61
0.27
0.51
0.51
0.40
0.35
0.48
0.23
0.34
0.41
0.28
0.35
0.53
0.29
0.69
0.41
0.46
-0.09
0.03
-0.02
0.13
-0.03
-0.01
-0.16
-0.04
-0.04
-0.05
-0.09
-0.05
0.55
0.23
0.24
0.71
0.56
0.23
1.71
2.48
1.64
2.40
1.88
1.85
1.50
2.19
1.39
1.68
1.63
1.49
0.93
1.58
1.00
2.07
1.16
1.30
USA
S.D
0.51
Variation over 2 year of book
value of equity in excess of net
income in %
Mean
Median
S.D
0.10
-0.02
0.68
202
Stock Prices And Implied Abnormal Earnings Growth
Singapore
Taiwan
Thaïland
Mean
5,83
6,95
5,63
6,57
0.45
0.48
0.34
0.45
0.34
0.40
0.25
0.34
0.50
0.44
0.36
0.45
-0.01
-0.05
-0.09
-0.02
-0.07
-0.07
-0.14
-0.08
0.35
0.23
0.32
0.38
1.90
1.79
1.66
1.93
1.51
1.57
1.38
1.59
1.25
1.13
1.25
1.30
The accounting measures of past growth were selected based on the methodology inspired by Hribar
and Yehuda (Hribar & Yehuda, 2008). Three basic variables were measured: the variation of sales over
2 years in %, variation of book value of equity in excess of net income in%, and the ratio of investment
over 2 years compared to past depreciation during these past years (measured by the items WS.Sales,
WS.TotalCommonEquity,
WS.NetIncome,
and
WS.CapitalExpendituresCFStmt
WS.DepreciationDeplAmortExpense of Worldscope database from Thomson Reuters). According to
the first and the third indicator, the emerging countries have experienced the sharpest growth.
These variables measuring the past growth have been combined into a synthetic indicator which varies
from 0 (lowest growth) to 1 (highest growth). The detailed calculation of this indicator is given in
Annex.
4. The Empirical Results
We comment, in the first paragraph, the different level of association between market values,
expected earnings and their expected variation while omitting the supposed impact of dividends. We,
then, discuss the possible effects of the bias associated with used forecasts. Finally, we propose a series
of estimates of the expected implicit rates of return derived from these association relations.
4.1 Association between market values and expected earnings without taking into account dividends
The estimation of the equation (7) requires a preliminary measurement of the rate r to calculate the
abnormal earnings growth. Since this rate is not directly observable and that it intervenes in the
calculation of expected earnings per share cum dividend, we initially ignore the impact of r ∙ DPS .
Table 3 provides an estimate for 18 countries studied. Expected earnings per share for the next year are
significantly associated with stock prices in all countries. The primary role of expected earnings in
valuation is therefore general, even if the intensity of the association varies considerably (8.77 on
average for emerging countries against 6.81 for the USA and 12.10 for other developed countries.
The increase in earnings per share is significantly associated with market value in the case of
developed countries but this is not always true in case of emerging countries (the coefficients are not
significant for Brazil and Malaysia).The average of these coefficients is 15.63 for USA, 19.79 for other
developed countries and 26.7 for emerging countries.
The coefficient associated with the composite measure of growth are mostly negative and nonsignificant in developed countries (-0.047 for the USA and on average -0.006 for others),with a notable
exception of Japan (0.188). This coefficient is positive on average in emerging markets (0.200) but
significant only for Hong Kong, Indonesia, Malaysia and Thailand. Note that according to the equation
(5), the expected sign for this variable depends on that of the term h. It can be positive and negative
according to the degree of persistence and depending on the rate of growth (c), speed (γ)and the ability
to persist (δ) which characterize the value creation potential of the firm. When it is negative (positive),
only the capitalization of the expected increase in the short-term earnings tends to over value (under
value) the share and this factor has made the necessary correction. The empirical results suggest that
during this period, growth in short terms earnings was not sustainable over a long period (except Japan,
which displays very poor performance). In contrast, on average, in the emerging countries, the shortterm variation of earnings does not fully realize long-term growth potential.
The coefficients of the variable size are significant in all countries. But it is negative in the USA
(-0.022) and in Korea and positive in emerging countries (0.124) or other developed countries (0.079).
The American sample is large and one that offers the greatest variety of business sizes.
203
International Journal of Economics and Financial Issues, Vol. 4, No. 1, 2014, pp.196-216
Table 3. Association between market values, expected earnings and growth
This table presents the estimated values of the coefficients and their T for a regression model whose dependent
variable is market capitalization at year end normalized by total assets, and the independent variables are expected
earnings per share for the coming year and expected earnings growth for the following year normalized by total
assets per share and a synthetic accounting variable measuring the past growth. The size was introduced as a
control variable. The regressions were carried out by country with dummies by period. The coefficients T were
calculated from “heteroskedasticity consistent standard errors”. The study period extends from 2001 to 2008.The
data come from Worldscope and IBES databases provided by Thomson Financial. The observations belonging to
extreme percentiles for the dependent variable and the first two independent variables have been eliminated.
Finally, we have conserved companies appearing at least three times during the period.
b1
6.810
EPS2-EPS1
T
b2
T
21.356 15.629 14.187
Growth Rank
Size
T
b4
T
R2
b3
-0.047 -1.014 -0.022 -3.423 0.423
Number of
F
Observations
354.609
5 333
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
12.922
8.916
8.085
14.564
13.253
15.635
9.975
13.479
15.080
10.496
15.259
17.328
17.161
50.469
11.951
23.884
0.040 0.416
0.273 2.423
-0.349 -3.772
0.028 0.341
0.071 0.931
0.188 9.095
-0.102 -1.038
-0.196 -1.494
0.092 6.495 0.751
0.114 6.775 0.642
0.073 6.599 0.545
0.068 7.762 0.704
0.054 4.579 0.760
0.056 12.805 0.745
0.119 10.035 0.577
0.058 4.253 0.750
158.052
111.390
71.331
148.086
84.716
900.015
104.262
96.495
12.104
19.792
-0.006
0.079
Brazil
China
Korea
Hong-Kong
Indonesia
Malaysia
Singapore
Taïwan
Thaïland
Emerging
countries
4.729
6.136
9.325
8.865
10.333
11.706
9.595
10.048
8.204
4.475 1.384
4.962 11.447
8.367 6.084
14.432 9.473
9.111 9.736
23.695 -0.412
13.413 12.575
27.407 8.152
10.124 6.868
8.771
7.256
EPS1
USA
32.073
12.206
8.533
21.376
23.849
21.149
17.493
21.653
5.353
3.717
6.033
6.792
5.985
13.787
7.509
5.786
0.695
2.025
2.828
5.853
3.336
-0.183
4.776
6.129
2.858
0.114
0.160
0.147
0.454
0.326
0.331
0.003
0.042
0.224
0.200
0.836
0.907
1.105
3.972
2.280
4.116
0.022
0.649
2.612
0.162 5.514 0.436
0.106 3.719 0.313
-0.036 -1.826 0.601
0.181 10.894 0.568
0.158 4.835 0.801
0.108 4.326 0.772
0.202 11.016 0.691
0.099 7.136 0.821
0.134 7.656 0.657
0.124
588
695
667
698
307
3 400
852
365
7 572
13.862
11.049
33.479
64.672
70.107
120.188
47.254
173.904
56.446
209
279
256
552
203
402
244
430
336
2 911
4.2 Quality of forecasts and association of variables.
The coverage of various stocks by financial analysts is certainly uneven in quantity and quality
according to the countries concerned. It is not, therefore, clear that the EPS forecast reported by IBES
constitute a measure of market expectations, endowed with a homogeneous quality. Table 4 provides a
series of measures of forecast errors characterizing each country at the end of the period. The average
absolute error represents 4.76% of average score in USA, 12.01% in other developed countries and
14.42% in emerging countries. The quality of forecasts is significantly higher in the USA. The
disparities among countries are strong: Italy and Brazil have the highest values, while Australia and
Taiwan have the lowest. The average error is positive, suggesting that analysts are pessimistic before
publication of earnings, either because they have been conducted by the management (“earning
guidance”) or because they are encouraged not to displease the firms: 0.93% of average score in USA,
2.95 % for other developed countries and 0.57% for emerging countries. However, disparities are very
large among countries. The averages are thus negative for Australia and Japan and for more than half of
emerging countries. It is possible that analysts’ behaviors are very heterogeneous. If during this period
FD regulation has, for example, prompted financial analysts to no longer express an unfounded
optimism to USA, the situation had been different in other countries. Therefore, it is possible that the
market holds expectations for the coming earnings per share, in some cases exceed the forecast reported
by IBES, and in other lower. The quality of estimates of association links between expected earnings
and market value is affected.
204
Stock Prices And Implied Abnormal Earnings Growth
Table 4. Forecast errors and initial optimism
This table presents the forecast errors for earnings per share for the year studied. The errors are estimated from the
available year end forecast. The values were normalized by total assets per share. The mean values provide an
estimate of bias, that of absolute values a measure of precision. These mean values were divided by the ratio of
expected EPS divided by total assets per share to obtain a measure of earnings in %. This estimate was preferred
to the mean of relative errors, given the presence of low values for certain earnings per share. The initial optimism
is measured by the ratio: difference between earnings per share forecast at the beginning of the year and EPS
realized in the previous year, divided by total assets per share at the beginning of the year. The study period
extends from 2001 to 2008.The data come from Worldscope and IBES databases provided by Thomson Financial.
The sample is that used previously, except for the measurement of initial optimism which lack certain
observations because of the lag of a year.
Error = (EPS real- EPS expected) / Total
assets per share
EPS
expected /
Total assets
per share
Ratios compared to mean
expected EPS
Mean
S.D
Mean
S.D
Mean
Mean Error
/ Mean
value
Mean
USA
0.09%
1.55%
0.46%
1.48%
9.68%
0.93%
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
0.28%
-0.04%
0.01%
0.35%
0.47%
-0.03%
0.21%
0.31%
1.50%
1.97%
1.24%
1.74%
2.55%
0.77%
1.84%
1.76%
0.89%
0.88%
0.67%
0.87%
1.00%
0.44%
0.96%
0.96%
1.24%
1.77%
1.05%
1.55%
2.40%
0.63%
1.59%
1.50%
6.97%
10.50%
7.23%
6.30%
5.45%
4.36%
7.91%
8.36%
0.20%
1.67%
0.83%
1.47%
Brazil
China
Korea
Hong Kong
Indonesia
Malaysia
Singapore
Taiwan
Thailand
Emerging countries
0.24%
-0.11%
-0.01%
0.00%
-0.57%
0.43%
0.51%
-0.15%
0.04%
0.04%
3.76%
1.51%
1.53%
2.91%
4.23%
4.00%
4.46%
1.76%
1.87%
2.89%
1.88%
0.86%
1.00%
1.37%
2.10%
1.50%
1.48%
1.05%
1.13%
1.38%
3.27%
1.25%
1.16%
2.57%
3.71%
3.73%
4.23%
1.42%
1.50%
2.54%
Value
Absolute value
Value
Initial optimism
Value
S.D
Mean
S.D
4.76%
17.22%
35.23%
4.05%
-0.39%
0.18%
5.57%
8.63%
-0.75%
2.61%
3.72%
12.69%
8.37%
9.28%
13.79%
18.27%
10.14%
12.09%
11.47%
20.05%
20.46%
14.44%
10.53%
5.56%
20.47%
12.02%
16.79%
83.92%
54.34%
41.55%
40.20%
54.94%
47.92%
30.50%
57.87%
7.13%
2.95%
12.01%
15.04%
51.40%
10.57%
7.44%
7.32%
8.95%
12.25%
9.16%
9.38%
10.76%
9.20%
9.45%
2.24%
-1.49%
-0.13%
-0.05%
-4.63%
4.68%
5.47%
-1.43%
0.45%
0.57%
17.82%
11.60%
13.68%
15.31%
17.17%
16.34%
15.84%
9.75%
12.26%
14.42%
39.33%
14.24%
15.96%
14.35%
16.97%
13.91%
11.18%
15.40%
16.80%
17.57%
267.16%
34.24%
38.80%
41.79%
42.54%
50.46%
41.84%
29.62%
50.44%
66.32%
The analysts’ behavior can vary according to the forecast horizon, with in the same country.
More it is distant, more it is difficult to verify the acuteness and more it is easy to be optimistic. Bartov
et al. (2002) suggest that analysts have an interest in optimism at the beginning of the year and then to
revise gradually their forecasts to end the year in pessimistic situation. They accumulate the advantage
of revealing flattering long term forecasts without exposing business leaders to announce disappointing
realized results. To characterize a possible initial optimism, we have calculated the gap in the beginning
of the year between the forecast earnings and last known earning per share, which is to say that of the
past year. All these measured have been normalized by total assets per share. The averages shown in
table 4 reflect a general optimism: the expected evolution expressed in % of average earnings for
concerned countries is of 17.22% in USA, 15.4% in other developed countries and 17.57% in emerging
countries.
The presence of a bias in the beginning of a period and a possibly different bias at the end of the
period doubly affect the measurement of the expected variation of earnings per share. If the forecast for
one year is optimistic and the short-term pessimistic, the variation between the two overestimates the
progression really expected by the market. If the short-term forecast is infected with a sense of
optimism, but that of one year is little concerned the same variation under estimate the actually
205
International Journal of Economics and Financial Issues, Vol. 4, No. 1, 2014, pp.196-216
anticipated growth. Finally, if only the forecast in the short term is biased, the impact is identical on
both variables: expected earnings and anticipated growth and these variables are found correlated. To
isolate the most severe effects of these manipulations of forecasts, we are inspired by the method used
by Tian (2009). We isolated in each country the forecast likely to be most affected by manipulation. To
do this, we have used two criteria. First, the forecast (firm-year) must be initially optimistic (the
expected earnings early in the year is higher than the earnings per share published last year). Second,
the revision of the forecast during the period must be abnormally pessimistic. To determine this second
point, we have regressed, for each country, the variation of the forecasts during the period (normalized
by total assets per share) on the stock return over the same period in order to eliminate the impact of the
information taken into account by the market. We, then, calculated the forecasting residuals and we
considered that if these residuals were negative and positive initial optimism, then we were faced with a
case which could be suspected of strong manipulation. Table 5 resumed the regression carried out in
table 3 but by combining a dummy variable taking the value 1 in a suspected case of manipulation and
variables related to earnings and variation of earnings.
The results obtained in the American market are as per expectations. The suspected cases of
manipulation of the forecasts are associated with a coefficient of valuation of expected earnings
significantly higher (a difference of 1.634). The market “would correct” the under estimation by the
analysts. The coefficients associated to expected variations of earnings is negative but nonsignificant
(-0.025). The correction coefficients related to growth is negative (-0.177) but becomes significant. In
contrast, the effects are negligible for other developed countries (with the exception of Germany). The
lack of results may be due to the small size of samples or less elaborated forecasts management by
analysts.
4.3 Estimation of expected implied rate of return and implied absnormal growth by country
Taking into account the dividends per share in the estimation of equation (7) requires knowledge of the
expected rate of return r. Moreover, if the theoretical model is verified; the same rate r should be equal
to
∙
+
−
∙
. To avoid having to assume zero dividends and thereby introducing a bias in the
estimation of the expected implicit rate of return, we proceed iteratively until this implicit rate for the
country concerned is equal to that which we used to calculate the abnormal earnings growth. The
estimates of the rate r and g were obtained from the coefficients of β1 and β2, only. This allows avoiding
taking into account the effects related to the manipulation of forecasts. It is likely that in these cases, the
market “corrects” the analysts’ forecasts and the coefficient obtained would be affected by this
correction (see (Easton & Sommers, 2007)).
The results obtained in paragraph 4.1 are confirmed in Table 6. In all countries expected earnings
by the analysts is strongly associated with market value. The coefficients vary across geographic zones
(7.27 in USA, 11.39 for other developed countries and 7.90 for emerging countries).The increase in
earnings per share is strongly associated with market value in the case of other developed countries but
this is not always the case in emerging countries. In the case of developed countries, using a PEG1
based heuristics helps to improve the analysis of the market value of securities, beyond the information
provided by the forward PE ratio. These two determinants can lead to overvaluation and require
correction (case of USA and Canada where the coefficients associated with the composite variable of
growth is significantly negative) and more rarely to an undervaluation (Japan).The results are mixed for
emerging countries. The information content of the expected abnormal increase in earnings per share
appears more limited. The coefficients associated are much lower (not meaningful for Brazil). The links
between market value and earnings are more difficult to identify solely from the next two years
earnings per share forecast. The reason can come from lower quality financial analysis. But also, the
values are certainly dependent on other factors describing the growth opportunities in long term. The
historical measurement of the past growth is of little use (coefficients significant in 3 cases out of 9).
The traditional valuation heuristics should therefore be handled with much more prudence in these
environments.
1
It is not, here, expected earnings per share but a measure of abnormal growth.
206
Stock Prices And Implied Abnormal Earnings Growth
Table 5. Association between market values, expected earnings, growth and manipulation of forecasts
This tables table presents the estimated values of the coefficients and their T for a regression model whose
dependent variable is market capitalization at year end normalized by total assets, and independent variables are
expected earnings per share for the coming year and expected earnings growth for the following year normalized
by total assets per share and a synthetic variable measuring the past growth. The size was introduced as a control
variable. The dummy variable Dm takes the value 1 if a manipulation index has been estimated. The regressions
were carried out by country with dummies by period. The coefficients T were calculated from “heteroskedasticity
consistent standard errors”. The study period extends from 2001 to 2008.The data come from Worldscope and
IBES databases provided by Thomson Financial. The observations belonging to extreme percentiles for the
dependent variables and the first two independent variables were eliminated. Finally, we have conserved
companies appearing at least three times during the period.
EPS1
USA
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
EPS1*Dm
T
21.679
12.409
9.320
8.056
14.431
12.949
15.510
10.070
13.431
13.778 5.618 1.594 36.372 5.322 -27.435
10.590 -1.520 -1.092 12.076 4.345 -0.155
14.982 0.573 0.759 7.784 4.824 2.266
16.952 -0.340 -0.304 22.804 6.355 -7.080
16.314 1.658 1.285 25.930 5.640 -8.797
47.160 0.694 1.293 22.000 13.032 -3.115
11.782 0.072 0.075 16.733 5.910 3.082
23.827 0.118 0.099 21.988 5.282 -1.788
12.022
B1m
1.634
Size
EPS2-EPS1
EPS2-EPS1*Dm Growth Rank
T
b4
T
T
B2
T
B2m
T
b3
2.859 17.299 13.712 -0.025 -0.009 -0.117 -2.279 0.028 3.521
b1
7.466
0.859
4.210 3.481 0.929
Brazil
6.088 4.836 -0.426
China
9.549 8.959 -2.615
Korea
8.447 14.082 2.908
Hong Kong
9.474 10.728 2.380
Indonesia
11.734 20.009 -0.114
Malaysia
9.590 14.592 2.080
Singapore
9.984 27.565 -0.152
Taiwan
8.207 10.109 0.325
Thailand
0.591
Emerging countries 8.587
20.711
-5.378
0.837 -1.138 -0.235
-0.233 8.651 2.541
-2.061 7.916 2.855
2.256 9.213 5.516
1.376 7.647 4.402
-0.151 -0.648 -0.255
1.165 12.042 5.283
-0.269 6.428 6.004
0.276 6.853 2.736
6.329
3.661
8.448
-2.347
-2.716
1.798
0.717
-1.830
8.716
0.706
1.906
-2.920
-0.013
0.671
-1.317
-1.255
-0.930
0.701
-0.297
0.062
0.251
-0.333
0.034
0.062
0.187
-0.103
-0.190
-0.004
0.683
0.533
-0.754
-0.535
0.228
0.173
-0.230
2.758
0.116
0.121
0.160
0.150
0.467
0.331
0.330
0.039
0.056
0.225
0.209
0.632
2.234
-3.559
0.422
0.791
9.076
-1.059
-1.511
Number
R2
F
of Obs.
0.463 433.489 5 533
0.090 6.564 0.751
0.113 6.831 0.642
0.073 6.646 0.545
0.065 7.556 0.704
0.056 4.563 0.760
0.057 12.252 0.745
0.120 10.163 0.577
0.057 4.233 0.750
158.052
111.390
71.331
148.086
84.716
900.015
104.262
96.495
0.079
588
695
667
698
307
3 400
852
365
7 572
0.880 0.151 5.332 0.436 13.862
0.904 0.108 3.629 0.313 11.049
1.163 -0.036 -1.839 0.601 33.479
4.172 0.187 11.351 0.568 64.672
2.286 0.164 4.977 0.801 70.107
4.006 0.108 4.292 0.772 120.188
0.335 0.209 11.209 0.691 47.254
0.876 0.098 7.447 0.821 173.904
2.607 0.135 7.520 0.657 56.446
0.125
The model appears to capture a hierarchy of expected rates of return, although estimates for
emerging markets remain very imprecise, country by country. The estimates of expected rates of return
are respectively of 10.9% for USA, 8% for other developed countries and 12.3% for the emerging
countries. Within the last two zones, the estimates vary across countries. For developed countries, the
expected returns are lowest in Japan (6.0%) and in the Eurozone (6.5% for France and 7% for
Germany) and the highest in Canada (11.4%) and Australia (10.1%) Among emerging countries, Brazil
(24.7%) and China (14.8%) topped. Malaysia (8.8%) , Taiwan(9.7%), Singapore (9.8%) and Korea
(9.9%) are in the tail. The implicit values of the parameter g which governs the abnormal earnings
growth are strongly negative (-0.406 for USA, on average of -0.595 for developed countries and 1.013
for emerging countries2 (-0.083 if we limit the extreme value to -1). It is interesting to note that no
estimates approach the hypothesis advanced by Ohlson and Juettner –Nauroth, namely a positive value
close to a long-term rate of growth.
2
This factor cannot be below -1, according to our model. No value appears significantly lower, except the case
of Malaysia.
207
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244
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336
2 911
International Journal of Economics and Financial Issues, Vol. 4, No. 1, 2014, pp.196-216
5. Robustness Tests
The valuation of assets depends in the model used on the discount rate required by the market.
Initially, we study the effects of two factors associated in the literature to the discount rate, the book to
market ratio and the size. Then, we take into account the differences in precision in the earnings per
share forecast. On the one hand, we can assume that more the forecasts are imprecise, the higher the
risk. On the other hand, the more forecasts are precise, the more consensuses of analysts is close to
market expectations. In both cases the measures of association should be affected. We, then, assume
that the coefficients of persistence (δ) and speed ( γ) that characterize this model may differ if the
abnormal growth is positive , or if it is negative. We replicate the test on a sub-sample composed solely
of positive expected variations. Finally, we conduct a direct estimate of the coefficient g which governs
the dynamics of the abnormal growth in earnings per share and compare with the implicit estimates
derived from the model.
5.1 Implied rate of return and risk factors
We classified the companies of each country into two subcategories, those whose studied factor is
low and those with high studied factor. The same method was used for the Book-to-Market ratio and for
the size. As these ratios vary country by country and year by year, we chose to classify by companies
and not by firm-year to avoid introducing the bias related to the period. The classification is carried out
according to the following protocol. For each country, firms in the sample 2008 were divided into two
groups around the median of used indicator (BM ratio or size). The same companies were taken in
2007. For those contained therein; the average ratio was performed for each of the sub-groups. If a
company appears in 2007 and does not exist in the sample in 2008, it is classified in the sub-population
to whom it is the nearest (the smallest distance from its indicator compared to the two averages). The
classification is retained for the following. The same approach is repeated in 2006 and beyond. Thus,
for each of the indicator (BM ratio or size), once a company is classified in her country as big or small.
The classification has the advantage of being independent of years and the inconvenience of not taking
into account a possible change in the characteristics of the company over the period.
From table 7 we can see that companies with the ratio “book to market” high generally have a low
coefficient associated with expected earnings (exceptions are Italy and United Kingdom for developed
countries and China for emerging countries): 2.92 against 6.27 to USA, 8.40 against 9.73 for other
developed countries and 4.19 against 7.72 for the emerging countries. The observation is consistent
with two explanations: (i) the PER are lower for these companies, (ii) the weight of PER is more
reduced in the valuation of shares. The test does not make it possible to decide between these two
reasons. The same observation can be made for the coefficient associated with the expected abnormal
variation of earnings per share. We have 4.52 against 17.48 for the USA, 8.68 against 20.80 for other
developed countries and 2.93 against 7.38 for emerging (with the exception of Italy and United
Kingdom). The contribution of amended PEG in the valuation is certainly much reduced for these
populations which probably contain many business of extremely poor performance. The expected
implied rate of return is high for companies with the high “book to market” ratio in the three geographic
zones. This hierarchy is consistent with the presence of a stronger risk factor for these sub-samples,
although the rate obtained for US companies in high ratio seems extremely high (24.8%). Finally, the
synthetic coefficient g, linked to persistence (δ) and the speed (γ) of abnormal growth is lower for
firms of “book to Market” ratio high. This is consistent with the presence of fewer opportunities for
growth, even in the existence of deceleration of expected abnormal earnings.
Companies of big size as a general rule have a higher coefficient associated with expected earnings
(the only exceptions are Australia and United Kingdom) :7.59 against 6.94 for USA , 12.23 against
10.30 for other developed countries and 8.64 against 6.59 for the emerging countries. The observation is
compatible with two explanations: (i) the PER are higher for these companies, (ii) the weight of PER is
greater in the valuation of shares. The same observation cannot be carried out for the coefficient
associated with the expected abnormal variation of earnings per share. We have a smaller coefficient for
large companies in USA (16.57 against 18.15) and the opposite in the other two zones (27.15 against
15.52 for other developed countries and 12.36 against 5.52 for emerging), with two exceptions
Canada and Korea. It is possible that the U.S. sample contains relatively more small performing
businesses, for which the market has more visibility on their future growth. The expected implied rate
of return is greater for small businesses within the 3 geographic zones. This hierarchy is consistent with
the presence of a risk factor related to the size, but the difference between the obtained rates for US
208
Stock Prices And Implied Abnormal Earnings Growth
companies is low (10.7% against 11.2%). Finally, the synthetic coefficient g, linked to persistence (δ)
and speed (γ) of abnormal growth is lower for small firms in other developed countries and emerging
countries and slightly higher in USA. This is consistent with the presence of more numerous growth
firms in the American sub-sample of small companies.
5.2 Implied return and precision of forecasts
The precision with which the analysts forecast the earnings per share can have a double influence
on the parameter of the valuation model. On one hand, the more the analysts’ forecasts are accurate, the
greater the correlation with market expectations. The measurement errors in dependent variables are
reduced. On the other hand, the forecast error may be related to risk of asset/share. The more it is
difficult to predict the earnings, the more high is the risk of a share. In this case, one can hypothesize
that the rate of return required by shareholders should be higher.
The forecast error is measured by the absolute value of the difference between the consensus of
analysts at year and the final earnings reported by IBES, so benefiting from homogenous measurement.
The difference is normalized, as is always the case, by the value of share in the beginning of year. For
each country separately, the companies were ranked according to these normalized differences in two
groups: those with high precision (values below the median) and those with a low precision.
The table 8 shows that in developed countries, the coefficient associated to expected earnings is
higher when the precision is high (8.38 against 6.53 in the USA, 12.26 against 10.59 in other developed
countries except the United Kingdom and Sweden). The differences are not significant in emerging
countries. This may be due to a lower rate of return required by shareholders and therefore a higher
PER or a better measure of expected earnings. The effect is less noticeable for emerging countries
where in general the link between the market value and expected earnings by the analysts is less strong.
The expected effect on the coefficient associated with the abnormal variation of earnings is more
ambiguous. On the one side, if the forecast error is correlated with a risk factor, the lower rate of return
increases the value of the coefficient. It is the same if the variation expected by the market is measured
with less error. On the other hand, it is possible that the companies whose performances are most
difficult to predict are those who benefit from more opportunities of growth. If these last are persistent,
then the parameter g of the model is larger and the coefficient associated higher. But it is also possible
that the reverse is true. We see in the table 8 that in the USA the coefficient is greater when the
precision is high (25.31 against 16.31) and that it is smaller in other developed countries (17.58 against
22.54 with the exception of Australia and Canada) and in most emerging countries.
5.3 Direct estimates of the rates of persistence of the abnormal earnings growth
One of the results presented concerns the dynamics of the “abnormal” growth of earnings per share.
Contrary to the hypothesis advanced by Ohlson and Juettner-Nauroth (2005), the theoretical model
developed in section 2 suggest that this abnormal growth does not necessarily follow a constant increase
in the long term, but on the contrary guided by various dynamics of which some are compatible with
limited persistence. The implicit measures that are derived from the estimates of the associated
coefficients of expected earnings and from expected abnormal growth are all consistent with the
hypothesis of limited persistence (the negative parameter g). In order to complement this empirical
result, we proceeded to the estimation of an autoregressive model with a lag of one year for expected
abnormal variation. The need to dispose of consecutive measurement has reduced the size of the
sample. The table 9 provides the obtained results.
It can be noted that for the most important sample, the USA, the two estimates of g are very close
(-0.394 and -0.399). In the case of other developed countries, the direct estimate is higher than implicit
(-0.364 and -0.521), while remaining in the order of the magnitude not too far, except for Canada. In the
case of emerging countries, the differences are more marked (-0.456 and -1.136) and especially the
found implicit values are smaller than -1. As the implicit values of the g are obtained from the
relationg = − , the errors contained in the implicit values most certainly come from an under
valuation of the coefficient β attached to the abnormal growth. The values found in emerging countries
and Canada are low in comparison to those obtained in other countries, growth in earnings per share are
less well anticipated by the consensus of the analysts. It is also noted that these samples are small in
size.
209
International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
Table 6. Expected implicit rates of return as a function of market value, expected earnings and growth
This tables presents the estimated values for the coefficients and their T for a regression model whose dependent variable is market capitalization at year-end normalized by total
assets, and the independent variables are the earnings per share for the coming year and increase in expected earnings for the following year plus the income generated by the
reinvestment of dividends and normalized by total assets per share, the same variable multiplied by a dummy variable indicating the suspected manipulation of forecast and a
synthetic accounting variable measuring the past growth. The size was introduced as a control variable, as well as dummy variable for each reporting year. The regression were
carried out by country , but taking into account all the years. The coefficients for year dummies are not reported. The coefficients T were calculated from “heteroskedasticity
consistent standard errors”. The study period extends from 2001 to 2008.The data come from Worldscope and IBES databases provided by Thomson Financial.
EPS1
[EPS1]*Dm
EPS2-EPS1+r.DPS1
1
7.265
T
21.071
1m
1.697
T
2.810
2
17.883
T
14.174
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
11.849
8.564
7.894
13.862
11.536
15.252
9.646
12.539
12.093
9.436
14.504
16.126
13.738
44.817
11.235
22.766
6.057
-1.473
0.608
-0.079
2.882
0.703
0.123
0.211
1.677
-1.155
0.782
-0.064
1.916
1.241
0.121
0.177
34.672
13.690
7.478
23.977
29.489
22.295
17.487
23.422
5.255
4.659
4.376
6.650
4.583
12.253
6.180
5.558
Brazil
China
Korea
Hong Kong
Indonesia
Malaysia
Singapore
Taiwan
Thailand
Emerging
countries
2.959
5.449
9.314
7.652
8.870
10.925
8.850
9.644
7.428
USA
11.393
7.899
1.129
2.168
4.258
8.547
12.866
11.636
17.689
12.679
26.248
9.397
1.013
-2.071
-2.574
2.325
1.684
0.253
3.264
-0.438
0.610
0.452
21.564
0.870
-0.687
-1.967
1.574
0.962
0.281
1.910
-0.684
0.501
4.400
8.860
8.250
11.551
8.740
5.415
13.770
6.491
8.501
8.442
[EPS2-EPS1+r.DPS1
]*Dm
T
2m
-0.113
-0.039
-25.987
1.101
2.823
-8.138
-13.781
-3.101
2.328
-2.114
-2.825
0.103
0.823
-1.483
-1.952
-0.944
0.549
-0.332
-5.859
1.580
2.883
3.167
6.691
4.383
2.278
6.503
6.109
3.643
1.843
14.428
-2.282
-0.238
4.698
-2.913
-6.916
7.982
-0.132
1.830
3
-0.140
T
-2.720
4
0.022
T
2.843
R
0.472
Implicites
measures
r
g
10.9%
-0.406
0.024
0.172
-0.359
0.016
0.018
0.180
-0.164
-0.226
0.250
1.551
-3.738
0.199
0.236
8.772
-1.659
-1.818
0.088
0.117
0.073
0.063
0.054
0.057
0.117
0.054
6.296
7.548
6.585
7.482
4.574
12.348
10.066
4.132
0.747
0.667
0.544
0.710
0.772
0.746
0.585
0.763
7.0%
10.1%
11.4%
6.5%
7.3%
6.0%
8.9%
7.0%
-0.342
-0.626
-1.056
-0.578
-0.390
-0.684
-0.549
-0.535
588
695
667
698
307
3 400
852
365
8.0%
-0.595
7 172
24.7%
14.8%
9.9%
11.2%
10.2%
8.8%
9.8%
9.7%
11.9%
-0.673
-0.615
-1.129
-0.662
-1.015
-2.018
-0.643
-1.486
-0.874
209
279
256
552
203
402
244
430
336
12.3%
-1.013
2 911
Growth Rank
-0.042
0.563
0.798
-0.731
-0.044
0.672
-0.707
-1.141
2.433
-0.022
0.141
0.160
0.138
0.432
0.284
0.353
-0.016
0.019
0.204
0.191
Size
2
0.078
1.030
0.908
1.098
4.031
1.980
4.279
-0.142
0.290
2.419
0.148
0.110
-0.037
0.188
0.152
0.113
0.205
0.096
0.136
0.123
5.188
3.747
-1.857
11.488
4.844
4.620
11.005
7.290
7.691
0.488
0.328
0.627
0.598
0.831
0.775
0.707
0.828
0.668
No. of
obs.
5 533
210
Stock Prices And Implied Abnormal Earnings Growth
Table 7. Expected implicit rates of return by country and risk factors
This table presents the estimated values of the first two coefficients and their T for a regression model whose dependent variables is market capitalization at year-end normalized
by total assets, and the independent variables are the expected earnings per share for coming year and expected increase in earnings for the following year plus the income
generated by the reinvestment of dividends and normalized by total assets per share, the same variables multiplied by a dummy variable indicating the suspected manipulation
of forecasts and a synthetic accounting variable measuring the past growth. The size was introduced as a control variable, as well as dummy variables for each reporting year.
The regression were carried out by country, but taking into account all the years. The coefficients T were calculated from “heteroskedasticity consistent standard errors”. The
study period extends from 2001 to 2008.The data come from Worldscope and IBES databases provided by Thomson Financial.
Panel A : With partition of the samples according to the Book to Market ratio
Low BM ratio
EPS1
EPS2-EPS1+r.DPS1
High BM ratio
Implicites measures
Number of
obs.
EPS1
EPS2-EPS1+r.DPS1
Implicites measures
Number of
obs.
1
6.272
T
14.696
2
17.484
T
11.081
r
12.0%
g
-0.359
3 338
1
2.920
T
12.139
2
4.524
T
6.368
r
24.8%
g
-0.646
2 195
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
10.963
7.590
6.555
13.714
8.745
16.081
3.668
10.518
9.225
6.931
9.101
12.491
13.028
37.295
11.507
11.997
40.292
12.799
8.079
27.881
6.761
24.938
8.578
37.076
5.225
3.910
3.615
5.593
2.575
11.310
8.645
6.154
7.2%
11.1%
13.1%
6.5%
10.6%
5.7%
18.9%
7.5%
-0.272
-0.593
-0.811
-0.492
-1.294
-0.645
-0.428
-0.284
349
405
361
386
179
1 848
440
188
8.129
5.241
5.806
8.201
15.468
9.177
6.865
8.287
12.224
6.735
11.833
13.285
13.684
24.815
6.412
14.176
6.211
4.502
2.272
7.279
18.228
9.647
15.764
5.544
2.276
1.552
2.104
3.650
2.507
6.354
5.360
3.153
11.3%
16.7%
16.2%
11.1%
6.0%
9.9%
11.5%
11.2%
-1.309
-1.164
-2.556
-1.127
-0.849
-0.951
-0.436
-1.495
239
290
306
312
128
1 552
412
177
10.1%
-0.602
4 156
8.397
11.7%
-1.236
3 416
Brazil
China
Korea
Hong Kong
Indonesia
Malaysia
Singapore
Taiwan
Thailand
Emerging countries
3.789
2.229
10.001
6.193
9.884
10.729
9.935
9.949
6.808
7.724
21.7%
25.2%
9.5%
13.0%
9.2%
8.9%
9.3%
9.5%
12.7%
13.2%
-1.008
-0.321
-1.858
-0.548
-0.911
-1.939
-1.210
-1.615
-0.823
-1.137
117
161
146
313
128
240
137
189
194
1 625
0.067
4.860
4.491
4.364
3.819
4.789
3.748
6.330
5.273
4.193
53.9%
19.5%
18.4%
21.3%
23.2%
nc
20.4%
14.8%
16.8%
23.5%
-0.020
-3.409
-0.883
-2.732
-1.810
nc
-0.666
-2.097
-1.265
-1.610
92
118
110
239
75
162
107
241
142
1 286
USA
9.729
20.801
2.423
1.212
6.925
8.490
11.678
11.770
8.075
16.932
6.206
3.757
6.951
5.383
11.296
10.855
5.534
8.209
6.161
8.278
7.380
1.058
1.614
1.673
5.268
4.274
1.531
2.229
3.874
2.279
8.681
0.090
8.535
4.880
10.192
9.396
12.720
6.704
19.591
14.138
3.325
1.426
5.087
1.597
2.110
-0.019
5.624
3.018
4.168
2.926
1.432
0.804
3.763
1.221
1.744
-0.162
3.276
4.323
3.592
211
International Journal of Economics and Financial Issues, Vol. 4, No. 1, 2014, pp.196-216
Panel B : With partition of the samples according to size
Small Firms
EPS1
USA
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
Brazil
China
Korea
Hong Kong
Indonesia
Malaysia
Singapore
Taiwan
Thailand
Emerging countries
EPS2-EPS1+r.DPS1
Big Firms
Implicites measures
Number of
obs.
EPS1
EPS2-EPS1+r.DPS1
Implicites measures
Number of
obs.
1
6.936
T
13.418
2
18.152
T
11.131
r
11.2%
g
-0.382
2 918
1
7.593
T
17.393
2
16.569
T
8.706
r
10.7%
g
-0.458
2 615
10.201
10.401
7.428
11.919
6.969
13.674
10.406
11.389
10.032
9.885
13.037
17.888
11.699
33.516
7.473
10.511
25.146
11.123
7.964
17.179
7.934
19.878
13.069
21.894
3.783
3.281
3.709
4.353
3.578
10.399
3.739
4.138
8.2%
8.8%
11.9%
7.6%
12.6%
6.7%
8.7%
7.7%
-0.406
-0.935
-0.933
-0.694
-0.878
-0.688
-0.796
-0.520
341
349
343
413
156
1 883
406
165
12.122
6.83
8.568
15.507
14.737
17.126
9.317
13.657
6.710
4.980
8.473
9.198
16.977
34.827
8.426
19.670
53.316
19.765
6.417
41.920
17.979
29.650
20.204
27.908
4.529
3.727
2.218
5.796
2.903
10.543
4.780
3.822
6.4%
11.1%
10.8%
5.6%
6.3%
5.3%
9.0%
6.5%
-0.227
-0.347
-1.335
-0.370
-0.820
-0.578
-0.461
-0.489
247
346
324
285
151
1 857
446
200
9.0%
-0.731
4 056
12.233
7.6%
-0.578
3 856
44.9%
15.4%
9.9%
12.9%
27.0%
10.7%
10.4%
10.2%
14.7%
17.3%
-0.322
-2.635
-0.824
-0.797
nc
-2.059
-0.652
-1.982
-1.954
-1.403
93
145
128
296
95
202
134
245
195
1 533
3.426
6.956
9.595
8.217
10.327
11.833
10.054
10.089
7.272
8.641
19.7%
12.5%
9.9%
9.8%
8.8%
7.9%
8.6%
9.1%
10.6%
10.8%
-0.411
-0.846
-2.006
-0.410
-0.849
-1.175
-0.565
-1.066
-0.358
-0.854
116
134
128
256
108
200
110
185
141
1 378
10.298
0.931
6.119
9.063
6.695
3.683
8.849
8.275
9.330
6.339
6.587
15.523
0.688
3.043
4.045
7.945
10.188
13.668
10.099
23.828
9.621
2.895
2.323
11.000
8.402
0.103
4.298
12.690
4.709
3.244
5.518
1.208
0.478
3.411
5.016
0.106
1.926
5.711
3.706
1.951
27.145
2.492
4.098
9.470
9.708
13.454
14.970
6.982
16.081
4.758
8.343
8.221
4.784
20.053
12.168
10.075
17.810
9.468
20.317
12.360
3.318
2.200
1.696
5.657
5.190
2.549
2.458
7.369
4.391
212
International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
Table 8. Expected implicit rates of return expected by country and forecast accuracy
This table presents the estimated values for the first two coefficients and their T for a regression model whose dependent variable is market capitalization at year-end
normalized by total assets , and the independent variables are the expected earnings per share for the coming year and expected earnings growth for the for the following year
plus the income generated by the reinvestment of dividends and normalized by total assets per share, the same variables multiplied by a dummy variable indicating the suspected
manipulation of the forecast and a synthetic accounting variable measuring the past growth. The size was introduced as a control variable, as well as dummy variables for each
reporting year. The regressions were carried out by country, but taking into account all the years. The coefficients T were calculated from “heteroskedasticity consistent standard
errors”. The study period extends from 2001 to 2008.The data come from Worldscope and IBES databases provided by Thomson Financial.
EPS1
1
8.378
T
11.686
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed
countries
13.101
9.459
10.296
16.182
12.670
16.325
8.235
11.808
11.191
11.584
11.480
14.264
23.010
26.352
9.232
17.732
Brazil
China
Korea
Hong Kong
Indonesia
Malaysia
Singapore
Taiwan
Thailand
Emerging countries
4.172
0.836
13.323
7.945
8.194
11.351
10.690
9.167
7.915
8.177
USA
12.260
High Precision
EPS2-EPS1+r.DPS1
Implicites measures
2
T
r
g
25.307
7.988
9.3%
-0.331
23.294
29.451
15.613
22.251
3.279
16.722
12.775
17.280
2.702
8.031
5.556
3.704
1.558
5.282
2.191
6.546
17.583
2.136
0.224
7.408
7.099
9.205
18.135
8.751
19.838
7.917
2.780
-1.165
3.946
19.689
4.133
6.274
14.396
9.557
7.184
7.422
0.521
-0.096
0.802
4.594
1.903
2.196
4.371
7.870
3.123
No. of obs.
EPS1
2 396
1
6.533
T
15.954
8.198
7.669
9.628
11.214
13.050
27.589
7.437
15.213
6.8%
8.4%
8.6%
5.7%
7.7%
5.8%
10.4%
7.6%
-0.562
-0.321
-0.659
-0.727
-3.864
-0.976
-0.645
-0.683
321
405
392
391
154
1 713
440
190
10.364
8.144
6.627
12.510
10.775
13.671
9.920
12.726
7.6%
-1.055
4 006
10.592
21.0%
nc
7.3%
10.1%
11.5%
8.4%
8.4%
9.9%
11.4%
11.0%
-1.506
nc
-3.377
-0.404
-1.983
-1.809
-0.743
-0.959
-1.102
-1.485
105
130
121
301
115
214
137
215
181
1 519
1.971
8.890
8.994
7.426
8.482
10.947
7.443
10.023
7.345
7.947
Low Precision
EPS2-EPS1+r.DPS1
Implicites measures
2
T
r
g
16.314
12.351
11.8%
-0.400
39.355
12.304
6.200
23.693
33.554
21.966
17.683
25.594
4.784
4.117
3.391
5.046
7.035
10.201
5.780
4.813
22.544
1.202
9.437
5.980
11.607
7.935
11.801
8.694
18.455
6.358
6.594
8.733
6.987
9.397
9.436
5.581
14.479
5.154
9.696
8.451
2.142
2.859
3.205
5.138
3.154
1.537
8.105
3.615
2.737
No. of obs.
3 137
7.5%
10.6%
13.4%
7.1%
7.5%
6.6%
8.7%
6.9%
-0.263
-0.662
-1.069
-0.528
-0.321
-0.622
-0.561
-0.497
267
309
275
307
153
1 687
412
175
8.5%
-0.565
3 585
26.8%
10.2%
10.3%
11.7%
10.6%
8.7%
11.1%
9.5%
11.8%
12.3%
-0.299
-1.018
-1.287
-0.790
-0.899
-1.961
-0.514
-1.945
-0.758
-1.052
104
149
135
251
88
188
107
215
155
1 392
213
International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
Table 9. Direct estimates of the rate of persistence of abnormal earnings growth
This table presents the estimated values of the coefficients and their T for a regression model whose dependent
variable is expected variation of abnormal earnings EPS2-EPS1+r.DPS1, normalized by total assets per share, and
the independent variable is the same variable but shifted by one period. The sample is identical to that of table
11.The estimates of cost of capital have been included. The coefficients T were calculated from
“heteroskedasticity consistent standard errors”. The study period extends from 2001 to 2008.The data come from
Worldscope and IBES databases provided by Thomson Financial.
EPS2-EPS1+r.DPS1
USA
1
0.606
Germany
Australia
Canada
France
Italy
Japan
United Kingdom
Sweden
Other developed countries
0.556
0.601
0.595
0.617
0.624
0.519
0.806
0.772
Brazil
China
Korea
Hong Kong
Indonesia
Malaysia
Singapore
Taiwan
Thailand
Emerging countries
0.605
0.404
0.466
0.688
0.738
0.540
0.579
0.439
0.450
0.545
T
24.945
Table 11
2
Number of
observations
R
0.460
g
-0.394
g implicite
-0.399
3 165
9.056
5.504
5.635
11.492
11.729
19.169
11.008
9.934
0.367
0.450
0.334
0.410
0.461
0.310
0.557
0.585
-0.444
-0.399
-0.405
-0.383
-0.376
-0.481
-0.194
-0.228
-0.364
-0.306
-0.676
-0.910
-0.544
-0.375
-0.587
-0.394
-0.377
-0.521
413
490
360
477
209
2 177
538
243
4 907
9.289
4.643
4.360
12.156
9.349
5.709
7.804
8.639
6.979
0.415
0.231
0.255
0.567
0.459
0.355
0.314
0.352
0.331
-0.395
-0.596
-0.534
-0.312
-0.272
-0.460
-0.421
-0.561
-0.550
-0.456
-0.263
-1.520
-1.313
-0.458
-0.621
-2.934
-0.835
-1.518
-0.766
-1.136
111
137
130
345
120
253
158
193
189
1 636
0.636
6. Conclusion
The model of the type AEG (for example, (Ohlson & Juettner-Nauroth, 2005), (Ohlson & Gao,
2006)) provide a parsimonious way of valuing shares by referring to two variables: expected earnings
per share and its expected “abnormal” growth. This paper shows that in the context of an international
comparison, estimates of these two variables obtained from two years forecasts prepared by financial
analysts (source: IBES) are significantly associated with the market values, at least in developed
countries. In the latter case, the expected earnings per share in 2 years has an information content that
complements a forecasting year. This observation is less evident in the case of the most of emerging
countries.
The theoretical model that we developed suggest that a valuation based on only these two variables
can lead to an under-valuation or to over-valuation according the type of growth experienced by the
companies. Using a synthetic measure based on past accounting data, we show that in some countries
(for example USA, Canada), a model of type AEG can lead to an over valuation of companies who
have experienced a strong growth in the recent past. The past dynamics cannot be prolonged over a long
period and a negative correction term is applied to these companies. In contrast, for others, the growth
has not yet led to an increase in earnings per share, enough to account for all the value creation potential
of these firms. In most of the emerging countries but also for certainly different reasons in Japan, a
214
Stock Prices And Implied Abnormal Earnings Growth
positive corrective term is proposed. The study outlines the limitation of AEG models to explain the
stock market values.
The results suggest that the abnormal growth of earning per share is unlikely to perpetuate by
following a constant pace of progress as was initially suggested by Ohlson and Juettner-Naurauth. On a
regular basis, the process that seems to best describe the expected evolution of this variable is
autoregressive in nature with limited persistence. The estimates for developed countries are coherent on
average (around 0.6 to USA and somewhat less for other developed countries). They remain very
inaccurate in the case of emerging countries, but still very low. By suggesting using a long term rate of
growth, O J-N contributes to propose specification of the models AEG strongly over estimating the
values of shares. In addition, by accepting these more complex dynamics for the expected variation of
abnormal earnings per share, we can deduce using the models AEG implicit values for the rate of return
expected by investors. The results emphasize that these estimates remain consistent with the various
commonly recognized factors of risk. Finally, we conclude with a practical remark: the combined use of
two heuristics that practitioners frequently use in valuation, namely the PE ratio and PEG ratio is
justified in the context of developed countries and unfortunately less powerful in emerging countries.
Acknowledgement
This research was supported by Lille School of Finance (Faculty of Finance, Bank and Accounting–
USDL and SKEMA Business School).The authors have received countless advices and comments from
Eric De Bodt. Errors and omissions remain their own responsibility.
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215
International Journal of Economics and Financial Issues
Vol. 4, No. 1, 2014, pp.196-216
ISSN: 2146-4138
www.econjournals.com
Annex
Method of calculation of the synthetic variable of growth and company rank according o their
stage of growth
Thesyntheticvariabley:isdefinedby:
y, =
x,, −x,
σ,
With
x =
Sales
Sales
− 1
x =
Equities − Equities
− NetIncome −NetIncome
Equities
x =
CapitalExpenditures + CapitalExpenditures
Depreciation + Depreciations
We have truncated their values using the fifth percentile as minimum and ninety fifth percentile as a
maximum, the reference populations are all profitable firms of the country concerned. I n order to
aggregate them; we calculated their values centered and reduced by country. The sum of the variable
refers to synthetic growth.
Companies are then classified each year t as a function of this synthetic variabley.Their rank is
normalized by the number of observations of the year and noted R , . In order to take into account the
persistent phenomenon, we have preferred an aggregate measure over two years.:RC , = (R , +
R , )/2. Finally, to facilitate interpretation, we calculated : 1 − RC , .
216